Abstract: Mechanisms are disclosed for estimating cardinality of group-by queries. A probability of occurrence of values is obtained for columns that satisfy the query occurring in tables from a trained machine learning model. A range selectivity is calculated based on a conditional probability of occurrence of the values. A set of valid generated sample tuples is generated from the trained machine learning model. A group-by selectivity is calculated by keeping the conditional probability of occurrence to obtain probabilities that a result set will have specific group-by column values associated with the tables while proceeding with progressive sampling. A sampling probability is calculated by normalizing the group-by selectivity by dividing the group-by selectivity by the range selectivity. The samples are filtered such that the samples having a sampling probability below a sampling probability threshold are filtered out. A sampling-based estimator is applied to the filtered samples set to estimate the cardinality.

Abstract: A system for managing documents, comprising: interfaces to a user interface, proving an application programming interface, a database of document images, a remote server, configured to communicate a text representation of the document from the optical character recognition engine to the report server, and to receive from the remote server a classification of the document; and logic configured to receive commands from the user interface, and to apply the classifications received from the remote server to the document images through the interface to the database. A corresponding method is also provided.

Abstract: A method for performing data management that includes generating, using a processor of an agent server, terms for structured data files using structured data profiling and terms for unstructured data files using unstructured data profiling, wherein the structured data files and the unstructured data files are stored in a storage; and managing a term list, wherein the term list stores terms generated by the processor, wherein the processor utilizes terms generated through structured data profiling in deriving terms generated through unstructured data profiling.

Abstract: Computer-implemented improved real estate search methods, systems, and computer-readable media are described.

Abstract: A method for inferring intent and discrepancies in a label coding scheme is described. The method includes compiling data indicating how one or more individuals labeled unstructured content according to the label coding scheme comprising a plurality of labels. The method also includes analyzing a context associated with a content labeled in a particular manner by the one or more individuals. The method further includes detecting discrepancies of meaning for a particular label used by the one or more individuals. The method also includes inferring a strategic thinking of the one or more individuals associated with the discrepancies of meaning detected for the particular label. The method further includes displaying recorded metadata associated with the strategic thinking and the discrepancies of meaning detected for the particular label between the one or more individuals regarding a coded dataset.

Abstract: Rapid development in digitization results in generation of huge amounts of unstructured text data by most organizations from several sources. A major drawback of using existing metrics in the data management is assessing quality of topics associated with context in a document. A processed dataset obtained from a raw dataset is mapped to obtain a relationship between one or more words from one or more topics. A word score is determined based on probability of number of constructs in sentences. At least one repetitive word from the one or more topics are determined. A topic score with degree of contextual association between the one or more words in each topic is determined by mean value of the word score. A contiguity score with degree of contextual association between the one or more topics is determined based on median value of the topic score to obtain one or more connected topics.

Abstract: Storing and retrieving media recordings in an object comprises a first method of storing a media recording comprising the following steps performed at an ingest component of a system: assigning a recording ID to the media recording; storing media data in one or more data objects in an object store, each carrying the recording ID; storing media metadata in an attribute object carrying the recording ID; computing a hash of the metadata; and storing the hash, the recording ID, a recording interval and a recording source in an index object. The first method further comprises concatenating the index object with an existing index object using a maintenance component. A second method is suitable for retrieving a media recording stored in an object store using the first method. A third method is suitable for performing maintenance on the object store by concatenating specific groups of index objects.

Abstract: A spatial auto-correlation clustering method for a remote correlation mode. By taking the degree of remote correlation between each spatial grid cell and an adjacent cell thereof into consideration, and on the basis of the definition of a local Moran index, an original value of a correlation coefficient is used without performing centralization processing, thereby improving a local Moran index calculation formula to obtain a new local indicator of spatial auto-correlation (LISAAC), such that the detection of a significant positive or negative remote correlation aggregation range is realized, and the identification of an abnormal value (that is, a non-significant or negative-value grid appears in a significant positive-value area, and a non-significant or positive-value grid appears in a significant negative-value area) is realized.

Abstract: Aspects of the invention include techniques for decomposing trend and seasonality components in a forecast of parametric time series data. A non-limiting example method includes receiving time series data that includes a plurality of values taken over a first period of time. A forecast is generated using the time series data. The forecast can include one or more predicted values over a second period of time. The forecast is decomposed into N components and 2N coalitions are defined for the N components. A coalition value is determined for each coalition of the 2N coalitions.

Abstract: The present invention concerns a method of encapsulating images in a file, wherein the method comprises determining a grouping type based on a capture mode of the images; generating a grouping data structure describing the images as a group, the grouping data structure comprising image identifiers of the images of the group; and embedding the grouping data structure, the grouping type and the images in the file.

Abstract: Interactive assistances for executing natural language queries to data sets may be performed. A natural language query may be received. Candidate entity linkages may be determined between an entity recognized in the natural language query and columns in data sets. The candidate linkages may be ranked according to confidence scores which may be evaluated to detect ambiguity for an entity linkage. Candidate entity linkages may be provided to a user via an interface to select an entity linkage to use as part of completing the natural language query.

Abstract: Various embodiments of the present disclosure provide for generating, updating, and/or otherwise managing an assent management system and its associated objects. An example embodiment is configured for accessing an asset management repository comprising a plurality of object type identifier nodes and a plurality of object attribute identifier nodes configured in a directed graph structure; receiving an object query comprising a selected object type identifier; traversing the directed graph structure to return a selected object type schema comprising an object attribute identifier node subset associated with the selected object type identifier; and outputting a selected object type interface component based on the selected object type schema for rendering to the object types registry interface.

Abstract: A computer-implemented method for performing application data consistency management among a plurality of computing devices within a communication network includes retrieving by a first device, application data from a second device. The application data includes an app ID and a first application version number of an app residing on the second device. A first database table is updated using an object type associated with the app ID and the first application version number. The object type identifies a database table schema of a data object used by the app and a plurality of data fields of the data object. Data stored by one or more of the plurality of data fields is synchronized with a third device based on a second application version number of the app residing on the third device and the first database table.

Abstract: A data system is provided for analyzing and maintaining data obtained from one or more data sources on which the data system depends. The system includes a primary database including current values used by the system and a collection of executable algorithms used to generate the data maintained in the primary database. In response to receiving a notification regarding a change in one of the data sources, a dependency database is used to establish an execution order for algorithms of the algorithm collection that are directly or indirectly dependent on the changed data. The algorithms identified in the execution order are then executed in accordance with the execution order and the corresponding result is stored in the primary database. The system may include data harvesters adapted to recognize changes in the data sources and to generate and transmit corresponding change notifications when such changes occur.

Abstract: According to one embodiment, a parameter optimization apparatus stores data sets which each include a first parameter value of a first number of dimensions and an observed value of an objective function corresponding to the first parameter value. The apparatus determines a search space of a second number of dimensions smaller than the first number of dimensions. The apparatus acquires one or more data sets each having a first parameter value present within a predetermined distance from the search space. The apparatus searches the search space for a first parameter value that may optimize the objective function, using a surrogate model of an objective function based on one or more data sets acquired.

Abstract: The present disclosure provides a method, system and computer program product for optimal query scheduling for resource utilization option. In an embodiment of the disclosure, a process for optimal query scheduling includes receiving in an information retrieval data processing system at a contemporaneous time, a request for deferred query execution of a specified query to a future time after the contemporaneous time. The method additionally includes determining a frequency of change of data corresponding to a field referenced in the specified query. Then, on condition that the frequency of change is below a threshold value, an intermediate time prior to the future time but after the contemporaneous time can be identified and the specified query scheduled for execution at the intermediate time instead of the future time. But, otherwise the specified query can be scheduled at the future time as originally requested.

Abstract: Systems and methods related to dynamically orchestrating execution of a protocol by generating one or more executors and one or more functions using a network controller based on the protocol are disclosed. In one example embodiment, there is provided a method of receiving a user-defined logic to allow the network controller to generate a dataset including a plurality of accumulators, abstract one or more executors and functions, and generate a set of protocols at the one or more functions to activate a respective application stage to fulfill the service request based on the logic in near real-time. Moreover, methods herein may include determining a telemetry and/or insight generation based, at least in part, on the dataset.

Abstract: The data linkage system 90 includes a learning device 70 which generates a score function, which is a function that scores proximity between a user with an action history in a first domain and a user with an action history in a second domain, and an estimation device 80 which estimates a user matched in the first domain and the second domain. The score calculation means 82 calculates a score for a pair of users who have an action history in a first domain and an action history in a second domain using a score function. The matching means 83 estimates the same user as the user in the first domain from among the users in the second domain based on magnitude of the calculated score.

Abstract: Generating a synthetic longitudinal dataset includes identifying subsequence patterns in records defining event sequences for patients. Feature vectors are determined, each characterizing a corresponding one of the records, based on the subsequence patterns. The feature vectors are embedded in a lower dimension space. A seed record is iteratively selected from among the records and in each iteration: subsequence patterns are identified in a subset of the records. Instances of subsequence patterns in the seed record are replaced with instances of similar subsequence patterns identified in the subset of the records to form a modified seed record. The iterations are repeated until all of the records have been selected as the seed record. The modified seed records are combined to form the synthetic dataset.

Abstract: Technologies are described for managing database queries based on bill of materials (BOM). For example, a set of database queries can be optimized (e.g., in terms of time and sequence of execution) based on a BOM explosion. In some implementations, database queries are managed by generating a BOM for an application programming interface (API) call. Various data structures can be created from the BOM, which can comprise procedure information, application and action information, and/or hierarchy information. A logical sequence of execution can be determined based, at least in part, on one or more of the data structures, where the logical sequence of execution comprises a plurality of database queries to execute the API call. The logical sequence of execution can be optimized to produce an optimized sequence of execution. The API call can be executed according to the optimized sequence of execution.